// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#ifndef EIGEN_GENERAL_PRODUCT_H
#define EIGEN_GENERAL_PRODUCT_H

namespace Eigen {

enum
{
    Large = 2,
    Small = 3
};

// Define the threshold value to fallback from the generic matrix-matrix product
// implementation (heavy) to the lightweight coeff-based product one.
// See generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemmProduct>
// in products/GeneralMatrixMatrix.h for more details.
// TODO This threshold should also be used in the compile-time selector below.
#ifndef EIGEN_GEMM_TO_COEFFBASED_THRESHOLD
// This default value has been obtained on a Haswell architecture.
#define EIGEN_GEMM_TO_COEFFBASED_THRESHOLD 20
#endif

namespace internal {

    template <int Rows, int Cols, int Depth> struct product_type_selector;

    template <int Size, int MaxSize> struct product_size_category
    {
        enum
        {
#ifndef EIGEN_GPU_COMPILE_PHASE
            is_large =
                MaxSize == Dynamic || Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD || (Size == Dynamic && MaxSize >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD),
#else
            is_large = 0,
#endif
            value = is_large ? Large : Size == 1 ? 1 : Small
        };
    };

    template <typename Lhs, typename Rhs> struct product_type
    {
        typedef typename remove_all<Lhs>::type _Lhs;
        typedef typename remove_all<Rhs>::type _Rhs;
        enum
        {
            MaxRows = traits<_Lhs>::MaxRowsAtCompileTime,
            Rows = traits<_Lhs>::RowsAtCompileTime,
            MaxCols = traits<_Rhs>::MaxColsAtCompileTime,
            Cols = traits<_Rhs>::ColsAtCompileTime,
            MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::MaxColsAtCompileTime, traits<_Rhs>::MaxRowsAtCompileTime),
            Depth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::ColsAtCompileTime, traits<_Rhs>::RowsAtCompileTime)
        };

        // the splitting into different lines of code here, introducing the _select enums and the typedef below,
        // is to work around an internal compiler error with gcc 4.1 and 4.2.
    private:
        enum
        {
            rows_select = product_size_category<Rows, MaxRows>::value,
            cols_select = product_size_category<Cols, MaxCols>::value,
            depth_select = product_size_category<Depth, MaxDepth>::value
        };
        typedef product_type_selector<rows_select, cols_select, depth_select> selector;

    public:
        enum
        {
            value = selector::ret,
            ret = selector::ret
        };
#ifdef EIGEN_DEBUG_PRODUCT
        static void debug()
        {
            EIGEN_DEBUG_VAR(Rows);
            EIGEN_DEBUG_VAR(Cols);
            EIGEN_DEBUG_VAR(Depth);
            EIGEN_DEBUG_VAR(rows_select);
            EIGEN_DEBUG_VAR(cols_select);
            EIGEN_DEBUG_VAR(depth_select);
            EIGEN_DEBUG_VAR(value);
        }
#endif
    };

    /* The following allows to select the kind of product at compile time
 * based on the three dimensions of the product.
 * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
    // FIXME I'm not sure the current mapping is the ideal one.
    template <int M, int N> struct product_type_selector<M, N, 1>
    {
        enum
        {
            ret = OuterProduct
        };
    };
    template <int M> struct product_type_selector<M, 1, 1>
    {
        enum
        {
            ret = LazyCoeffBasedProductMode
        };
    };
    template <int N> struct product_type_selector<1, N, 1>
    {
        enum
        {
            ret = LazyCoeffBasedProductMode
        };
    };
    template <int Depth> struct product_type_selector<1, 1, Depth>
    {
        enum
        {
            ret = InnerProduct
        };
    };
    template <> struct product_type_selector<1, 1, 1>
    {
        enum
        {
            ret = InnerProduct
        };
    };
    template <> struct product_type_selector<Small, 1, Small>
    {
        enum
        {
            ret = CoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<1, Small, Small>
    {
        enum
        {
            ret = CoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<Small, Small, Small>
    {
        enum
        {
            ret = CoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<Small, Small, 1>
    {
        enum
        {
            ret = LazyCoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<Small, Large, 1>
    {
        enum
        {
            ret = LazyCoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<Large, Small, 1>
    {
        enum
        {
            ret = LazyCoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<1, Large, Small>
    {
        enum
        {
            ret = CoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<1, Large, Large>
    {
        enum
        {
            ret = GemvProduct
        };
    };
    template <> struct product_type_selector<1, Small, Large>
    {
        enum
        {
            ret = CoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<Large, 1, Small>
    {
        enum
        {
            ret = CoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<Large, 1, Large>
    {
        enum
        {
            ret = GemvProduct
        };
    };
    template <> struct product_type_selector<Small, 1, Large>
    {
        enum
        {
            ret = CoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<Small, Small, Large>
    {
        enum
        {
            ret = GemmProduct
        };
    };
    template <> struct product_type_selector<Large, Small, Large>
    {
        enum
        {
            ret = GemmProduct
        };
    };
    template <> struct product_type_selector<Small, Large, Large>
    {
        enum
        {
            ret = GemmProduct
        };
    };
    template <> struct product_type_selector<Large, Large, Large>
    {
        enum
        {
            ret = GemmProduct
        };
    };
    template <> struct product_type_selector<Large, Small, Small>
    {
        enum
        {
            ret = CoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<Small, Large, Small>
    {
        enum
        {
            ret = CoeffBasedProductMode
        };
    };
    template <> struct product_type_selector<Large, Large, Small>
    {
        enum
        {
            ret = GemmProduct
        };
    };

}  // end namespace internal

/***********************************************************************
*  Implementation of Inner Vector Vector Product
***********************************************************************/

// FIXME : maybe the "inner product" could return a Scalar
// instead of a 1x1 matrix ??
// Pro: more natural for the user
// Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
// product ends up to a row-vector times col-vector product... To tackle this use
// case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);

/***********************************************************************
*  Implementation of Outer Vector Vector Product
***********************************************************************/

/***********************************************************************
*  Implementation of General Matrix Vector Product
***********************************************************************/

/*  According to the shape/flags of the matrix we have to distinghish 3 different cases:
 *   1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
 *   2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
 *   3 - all other cases are handled using a simple loop along the outer-storage direction.
 *  Therefore we need a lower level meta selector.
 *  Furthermore, if the matrix is the rhs, then the product has to be transposed.
 */
namespace internal {

    template <int Side, int StorageOrder, bool BlasCompatible> struct gemv_dense_selector;

}  // end namespace internal

namespace internal {

    template <typename Scalar, int Size, int MaxSize, bool Cond> struct gemv_static_vector_if;

    template <typename Scalar, int Size, int MaxSize> struct gemv_static_vector_if<Scalar, Size, MaxSize, false>
    {
        EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Scalar* data()
        {
            eigen_internal_assert(false && "should never be called");
            return 0;
        }
    };

    template <typename Scalar, int Size> struct gemv_static_vector_if<Scalar, Size, Dynamic, true>
    {
        EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Scalar* data() { return 0; }
    };

    template <typename Scalar, int Size, int MaxSize> struct gemv_static_vector_if<Scalar, Size, MaxSize, true>
    {
        enum
        {
            ForceAlignment = internal::packet_traits<Scalar>::Vectorizable,
            PacketSize = internal::packet_traits<Scalar>::size
        };
#if EIGEN_MAX_STATIC_ALIGN_BYTES != 0
        internal::plain_array<Scalar, EIGEN_SIZE_MIN_PREFER_FIXED(Size, MaxSize), 0, EIGEN_PLAIN_ENUM_MIN(AlignedMax, PacketSize)> m_data;
        EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
#else
        // Some architectures cannot align on the stack,
        // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
        internal::plain_array<Scalar, EIGEN_SIZE_MIN_PREFER_FIXED(Size, MaxSize) + (ForceAlignment ? EIGEN_MAX_ALIGN_BYTES : 0), 0> m_data;
        EIGEN_STRONG_INLINE Scalar* data()
        {
            return ForceAlignment ?
                       reinterpret_cast<Scalar*>((internal::UIntPtr(m_data.array) & ~(std::size_t(EIGEN_MAX_ALIGN_BYTES - 1))) + EIGEN_MAX_ALIGN_BYTES) :
                       m_data.array;
        }
#endif
    };

    // The vector is on the left => transposition
    template <int StorageOrder, bool BlasCompatible> struct gemv_dense_selector<OnTheLeft, StorageOrder, BlasCompatible>
    {
        template <typename Lhs, typename Rhs, typename Dest> static void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha)
        {
            Transpose<Dest> destT(dest);
            enum
            {
                OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor
            };
            gemv_dense_selector<OnTheRight, OtherStorageOrder, BlasCompatible>::run(rhs.transpose(), lhs.transpose(), destT, alpha);
        }
    };

    template <> struct gemv_dense_selector<OnTheRight, ColMajor, true>
    {
        template <typename Lhs, typename Rhs, typename Dest>
        static inline void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha)
        {
            typedef typename Lhs::Scalar LhsScalar;
            typedef typename Rhs::Scalar RhsScalar;
            typedef typename Dest::Scalar ResScalar;
            typedef typename Dest::RealScalar RealScalar;

            typedef internal::blas_traits<Lhs> LhsBlasTraits;
            typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
            typedef internal::blas_traits<Rhs> RhsBlasTraits;
            typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;

            typedef Map<Matrix<ResScalar, Dynamic, 1>, EIGEN_PLAIN_ENUM_MIN(AlignedMax, internal::packet_traits<ResScalar>::size)> MappedDest;

            ActualLhsType actualLhs = LhsBlasTraits::extract(lhs);
            ActualRhsType actualRhs = RhsBlasTraits::extract(rhs);

            ResScalar actualAlpha = combine_scalar_factors(alpha, lhs, rhs);

            // make sure Dest is a compile-time vector type (bug 1166)
            typedef typename conditional<Dest::IsVectorAtCompileTime, Dest, typename Dest::ColXpr>::type ActualDest;

            enum
            {
                // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
                // on, the other hand it is good for the cache to pack the vector anyways...
                EvalToDestAtCompileTime = (ActualDest::InnerStrideAtCompileTime == 1),
                ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
                MightCannotUseDest = ((!EvalToDestAtCompileTime) || ComplexByReal) && (ActualDest::MaxSizeAtCompileTime != 0)
            };

            typedef const_blas_data_mapper<LhsScalar, Index, ColMajor> LhsMapper;
            typedef const_blas_data_mapper<RhsScalar, Index, RowMajor> RhsMapper;
            RhsScalar compatibleAlpha = get_factor<ResScalar, RhsScalar>::run(actualAlpha);

            if (!MightCannotUseDest)
            {
                // shortcut if we are sure to be able to use dest directly,
                // this ease the compiler to generate cleaner and more optimzized code for most common cases
                general_matrix_vector_product<Index,
                                              LhsScalar,
                                              LhsMapper,
                                              ColMajor,
                                              LhsBlasTraits::NeedToConjugate,
                                              RhsScalar,
                                              RhsMapper,
                                              RhsBlasTraits::NeedToConjugate>::run(actualLhs.rows(),
                                                                                   actualLhs.cols(),
                                                                                   LhsMapper(actualLhs.data(), actualLhs.outerStride()),
                                                                                   RhsMapper(actualRhs.data(), actualRhs.innerStride()),
                                                                                   dest.data(),
                                                                                   1,
                                                                                   compatibleAlpha);
            }
            else
            {
                gemv_static_vector_if<ResScalar, ActualDest::SizeAtCompileTime, ActualDest::MaxSizeAtCompileTime, MightCannotUseDest> static_dest;

                const bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha) == RealScalar(0));
                const bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;

                ei_declare_aligned_stack_constructed_variable(ResScalar, actualDestPtr, dest.size(), evalToDest ? dest.data() : static_dest.data());

                if (!evalToDest)
                {
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
                    Index size = dest.size();
                    EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
                    if (!alphaIsCompatible)
                    {
                        MappedDest(actualDestPtr, dest.size()).setZero();
                        compatibleAlpha = RhsScalar(1);
                    }
                    else
                        MappedDest(actualDestPtr, dest.size()) = dest;
                }

                general_matrix_vector_product<Index,
                                              LhsScalar,
                                              LhsMapper,
                                              ColMajor,
                                              LhsBlasTraits::NeedToConjugate,
                                              RhsScalar,
                                              RhsMapper,
                                              RhsBlasTraits::NeedToConjugate>::run(actualLhs.rows(),
                                                                                   actualLhs.cols(),
                                                                                   LhsMapper(actualLhs.data(), actualLhs.outerStride()),
                                                                                   RhsMapper(actualRhs.data(), actualRhs.innerStride()),
                                                                                   actualDestPtr,
                                                                                   1,
                                                                                   compatibleAlpha);

                if (!evalToDest)
                {
                    if (!alphaIsCompatible)
                        dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size());
                    else
                        dest = MappedDest(actualDestPtr, dest.size());
                }
            }
        }
    };

    template <> struct gemv_dense_selector<OnTheRight, RowMajor, true>
    {
        template <typename Lhs, typename Rhs, typename Dest> static void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha)
        {
            typedef typename Lhs::Scalar LhsScalar;
            typedef typename Rhs::Scalar RhsScalar;
            typedef typename Dest::Scalar ResScalar;

            typedef internal::blas_traits<Lhs> LhsBlasTraits;
            typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
            typedef internal::blas_traits<Rhs> RhsBlasTraits;
            typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
            typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;

            typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
            typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);

            ResScalar actualAlpha = combine_scalar_factors(alpha, lhs, rhs);

            enum
            {
                // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
                // on, the other hand it is good for the cache to pack the vector anyways...
                DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime == 1 || ActualRhsTypeCleaned::MaxSizeAtCompileTime == 0
            };

            gemv_static_vector_if<RhsScalar, ActualRhsTypeCleaned::SizeAtCompileTime, ActualRhsTypeCleaned::MaxSizeAtCompileTime, !DirectlyUseRhs> static_rhs;

            ei_declare_aligned_stack_constructed_variable(
                RhsScalar, actualRhsPtr, actualRhs.size(), DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());

            if (!DirectlyUseRhs)
            {
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
                Index size = actualRhs.size();
                EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#endif
                Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
            }

            typedef const_blas_data_mapper<LhsScalar, Index, RowMajor> LhsMapper;
            typedef const_blas_data_mapper<RhsScalar, Index, ColMajor> RhsMapper;
            general_matrix_vector_product<Index,
                                          LhsScalar,
                                          LhsMapper,
                                          RowMajor,
                                          LhsBlasTraits::NeedToConjugate,
                                          RhsScalar,
                                          RhsMapper,
                                          RhsBlasTraits::NeedToConjugate>::
                run(actualLhs.rows(),
                    actualLhs.cols(),
                    LhsMapper(actualLhs.data(), actualLhs.outerStride()),
                    RhsMapper(actualRhsPtr, 1),
                    dest.data(),
                    dest.col(0).innerStride(),  //NOTE  if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166)
                    actualAlpha);
        }
    };

    template <> struct gemv_dense_selector<OnTheRight, ColMajor, false>
    {
        template <typename Lhs, typename Rhs, typename Dest> static void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha)
        {
            EIGEN_STATIC_ASSERT((!nested_eval<Lhs, 1>::Evaluate), EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE);
            // TODO if rhs is large enough it might be beneficial to make sure that dest is sequentially stored in memory, otherwise use a temp
            typename nested_eval<Rhs, 1>::type actual_rhs(rhs);
            const Index size = rhs.rows();
            for (Index k = 0; k < size; ++k) dest += (alpha * actual_rhs.coeff(k)) * lhs.col(k);
        }
    };

    template <> struct gemv_dense_selector<OnTheRight, RowMajor, false>
    {
        template <typename Lhs, typename Rhs, typename Dest> static void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha)
        {
            EIGEN_STATIC_ASSERT((!nested_eval<Lhs, 1>::Evaluate), EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE);
            typename nested_eval<Rhs, Lhs::RowsAtCompileTime>::type actual_rhs(rhs);
            const Index rows = dest.rows();
            for (Index i = 0; i < rows; ++i) dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum();
        }
    };

}  // end namespace internal

/***************************************************************************
* Implementation of matrix base methods
***************************************************************************/

/** \returns the matrix product of \c *this and \a other.
  *
  * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().
  *
  * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
  */
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Product<Derived, OtherDerived> MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived>& other) const
{
    // A note regarding the function declaration: In MSVC, this function will sometimes
    // not be inlined since DenseStorage is an unwindable object for dynamic
    // matrices and product types are holding a member to store the result.
    // Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
    enum
    {
        ProductIsValid = Derived::ColsAtCompileTime == Dynamic || OtherDerived::RowsAtCompileTime == Dynamic ||
                         int(Derived::ColsAtCompileTime) == int(OtherDerived::RowsAtCompileTime),
        AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
        SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived, OtherDerived)
    };
    // note to the lost user:
    //    * for a dot product use: v1.dot(v2)
    //    * for a coeff-wise product use: v1.cwiseProduct(v2)
    EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
                        INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
    EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
                        INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
    EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
#ifdef EIGEN_DEBUG_PRODUCT
    internal::product_type<Derived, OtherDerived>::debug();
#endif

    return Product<Derived, OtherDerived>(derived(), other.derived());
}

/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
  *
  * The returned product will behave like any other expressions: the coefficients of the product will be
  * computed once at a time as requested. This might be useful in some extremely rare cases when only
  * a small and no coherent fraction of the result's coefficients have to be computed.
  *
  * \warning This version of the matrix product can be much much slower. So use it only if you know
  * what you are doing and that you measured a true speed improvement.
  *
  * \sa operator*(const MatrixBase&)
  */
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Product<Derived, OtherDerived, LazyProduct>
MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived>& other) const
{
    enum
    {
        ProductIsValid = Derived::ColsAtCompileTime == Dynamic || OtherDerived::RowsAtCompileTime == Dynamic ||
                         int(Derived::ColsAtCompileTime) == int(OtherDerived::RowsAtCompileTime),
        AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
        SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived, OtherDerived)
    };
    // note to the lost user:
    //    * for a dot product use: v1.dot(v2)
    //    * for a coeff-wise product use: v1.cwiseProduct(v2)
    EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
                        INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
    EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
                        INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
    EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)

    return Product<Derived, OtherDerived, LazyProduct>(derived(), other.derived());
}

}  // end namespace Eigen

#endif  // EIGEN_PRODUCT_H
